Mea - Prediction of maximum expected accuracy RNA secondary structures
Supplemental material of manuscript "The Trouble with Long Range Base Pairs in RNA Folding" by
The Students of the Bioinformatics Computer Lab 2013,
Fabian Amman,
Stephan H. Bernhart,
Gero Dose,
Jing Qin,
Peter F. Stadler, and
Sebastian Will
Mea was developed as part of the lab class "Bioinformatik von RNA- und Proteinstrukturen (Praktikum, Modul 10-202-2208)". The package predicts maximum expected accuracy (MEA) RNA secondary structures from dot plots of RNAs while correcting the score in dependence of base pair span. Furthermore, it provides tools to evaluate predictions and optimize parameters.
Download
Mea is free software (GNU GPL 3). Please use the newest release unless you know what you are doing. Older releases are available below for reference.
mea-0.6.4 source [tar.gz]
Version 0.6.x adds slide rule and conflicts rule for comparisons to
the reference structure; these are turned on by default. 0.6.4
corrects major bugs in the structure comparison of 0.6; the
prediction itself is unchanged.
The package can be
compiled and installed in the common autotool's way by
./configure; make; make install.
Old releases
mea-0.5 source [tar.gz]
Version 0.5 enables comparing two structures w/o folding
(option --structure). Structure comparison is buggy:(
mea-0.4 source [tar.gz]
Version 0.4 has been used to produce the published results.
Mea package tools
-
mea [options] dotplot
predict mea structure from dot plot; control base pair penalty by parameters alpha, beta, gamma, and delta -
mea_eval
evaluate mea prediction in decpendence of parameters, given reference data -
mea_mix [options] dotplot1 dotplot2
predict mea structure by mixing two dot plots; control mixing weights by gamma1 and gamma2
Since release 0.5 the tool supports the general comparison of a given "predicted" structure to a "reference" structure by confusion matrix, F1-score, and MCC (Mathew's correlation coefficient.)
Furthermore, the package allows to compile a library mea-eval-R.so; this lib can be imported into R, where it enables optimizing parameters using R functionality.
Please call tools with help option to learn more about their parameters. Dot plots are generally read from files in ViennaRNA's "dp.ps" format.